Point Cloud Classification on ModelNet-C Unaugmented (test) benchmark leaderboard · SOTA2 Research

Point Cloud Classification on ModelNet-C Unaugmented (test)

93.9Overall AccuracySimpleView

Evaluation Results

Method	Links
SimpleView2023.03		93.9	1.047	0.872	0.715	1.242	1.357	0.983	0.844	1.316
CurveNet2023.03		93.8	0.927	0.872	0.725	0.71	1.024	1.346	1	0.809
EPiC2023.03		93.6	0.704	0.936	0.864	0.315	0.478	0.295	0.862	1.177
EPiC2023.03		93.6	0.75	0.915	1.057	0.323	0.44	0.281	0.902	1.33
PAConv2023.03		93.6	1.104	0.904	1.465	1	1.005	1.085	1.298	0.967
GDANet2023.03		93.4	0.892	0.83	0.839	0.794	0.894	0.871	1.036	0.981
EPiC2023.03		93.4	0.646	0.894	0.851	0.306	0.435	0.285	0.735	1.019
EPiC2023.03		93	0.669	1	0.68	0.331	0.498	0.349	0.807	1.019
PCT2023.03		93	0.925	0.872	0.87	0.528	1	0.78	1.385	1.042
RPC2023.03		93	0.863	0.84	0.892	0.492	0.797	0.929	1.011	1.079
PointNet++2023.03		93	1.072	0.872	1.177	0.641	1.802	0.614	0.993	1.405
DGCNN2023.03		92.6	1	1	1	1	1	1	1	1
RSCNN2023.03		92.3	1.13	1.074	1.171	0.806	1.517	0.712	1.153	1.479
EPiC2023.03		92.1	0.742	1.245	0.617	0.363	0.585	0.495	1.029	0.86
PointNet2023.03		90.7	1.422	1.266	0.642	0.5	1.072	2.98	1.593	1.902